Search

BackgroundType 2 diabetes mellitus (T2DM) is a chronic and progressive condition defined by hyperglycemia caused by abnormalities in insulin production, insulin receptor sensitivity, or both. Several studies have revealed that higher body mass index (BMI) is associated with increasing risk of developing diabetes. In this study, we perform a protocol for systematic review to explore metabolite biomarkers that could be used to identify T2DM in obese subjects.MethodsThe protocol of this review was registered in PROSPERO (CRD42023405518). Three databases, EMBASE, PubMed, and Web of Science were selected to collect potential literature from their inceptions to July December 2023. Data for collection will include title, authors, study subjects, publication date, sample size, detection and analytical platforms, participant characteristics, biological samples, confounding factors, methods of statistical analysis, the frequency and directions of changes in potential metabolic biomarkers, and major findings. Pathway analysis of differential metabolites will be performed with MetaboAnalyst 5.0 based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Human Metabolome Database.ResultsThe results of this systematic review will be published in a peer-reviewed journal.ConclusionThis systematic review will summarize the potential biomarkers and metabolic pathways to provide a new reference for the prevention and treatment of T2DM in obese subjects.

The front retaining wall (FRW) is an effective facility of selective withdrawal. Previous research has not estimated the effect of FRWs on the thermal regimes of reservoirs and outflow temperature, which are crucial to reservoir ecology. For this purpose, taking the Dongqing Reservoir as a case study, a two-dimensional hydrodynamic CE-QUAL-W2 model was configured for the typical channel-type reservoir in the southwestern Guizhou Province, to better understand the influence of FRWs on the thermal structure and outflow temperature. The simulated data from January to September 2017 showed that FRWs can change the vertical temperature distribution during the stratification period, accelerate the upper warmer water release and thus decrease the strength of thermal stratification. The stratification structure changed from a single thermocline to double thermoclines in August. An FRW resulted in an average 11.8 m increase in the thickness of the hypolimnion and a 1.2°C decrease in the thickness of the thermocline layer. An FRW increased the outflow temperature by 0.4°C and raised the withdrawal elevation by 16 m on average. The longitudinal velocity increased compared with the non-FRW condition, while the maximum velocity position moved up. In addition, FRWs can continuously obtain surface warmer water without manual operation and have low investment and good construction conditions. This study can provide an available selective withdrawal idea for reservoirs with similar hydraulic conditions.

Comparing DNA or protein sequences plays an important role in the functional analysis of genomes. Despite many methods available for sequences comparison, few methods retain the information content of sequences. We propose a new approach, the Yau-Hausdorff method, which considers all translations and rotations when seeking the best match of graphical curves of DNA or protein sequences. The complexity of this method is lower than that of any other two dimensional minimum Hausdorff algorithm. The Yau-Hausdorff method can be used for measuring the similarity of DNA sequences based on two important tools: the Yau-Hausdorff distance and graphical representation of DNA sequences. The graphical representations of DNA sequences conserve all sequence information and the Yau-Hausdorff distance is mathematically proved as a true metric. Therefore, the proposed distance can preciously measure the similarity of DNA sequences. The phylogenetic analyses of DNA sequences by the Yau-Hausdorff distance show the accuracy and stability of our approach in similarity comparison of DNA or protein sequences. This study demonstrates that Yau-Hausdorff distance is a natural metric for DNA and protein sequences with high level of stability. The approach can be also applied to similarity analysis of protein sequences by graphic representations, as well as general two dimensional shape matching.